"Tools and methods for analyzing Google Sheets data" matching MCP servers:

Enables generating JSON Schema from sample data, generating TypeScript types, validating data against schemas, creating mock data from schemas, and comparing schemas for differences.

Webhook management and testing tools for AI agents. Provides tools for sending, validating, generating, and debugging webhooks.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Enables validating JSON/JSONC, getting/setting values with jq-like paths, pretty-printing or minifying, validating against Ajv JSON Schema, and diffing local files or inline strings without network calls.

Enables coding agents to run Playwright e2e tests, validate Supabase RLS policies with role-based SQL, typecheck TypeScript, execute npm scripts with parsed test output, and validate Next.js builds, all through a structured MCP interface.

Thin HTTP wrapper for the Generate-Data.com API, enabling data generation, schema proposal, and field type listing through MCP tools.

MCP server providing code review, auto-fix, test running, linting, formatting, and refactor suggestions for Claude Code.

Provides 32 remote tools that let agents validate common data formats, optimize or minify code and content, and generate synthetic test data such as fake records, IDs, and passwords.

Provides a hand-written MCP server integrated with a LangGraph agent to benchmark multiple agent topologies and measure their failure rates.

Code linting and style checking tools for AI agents, exposed as an MCP server. Supports style checks, naming conventions, complexity analysis, dead code detection, and import analysis.

Bridges AI agents with VS Code's debugger, enabling breakpoint management, step execution, variable inspection, and stack tracing via CLI commands.

Provides AI agents with web accessibility analysis tools via MCP, enabling checks for alt text, heading hierarchy, color contrast, ARIA validation, and form accessibility.

Enables AI agents to interact with Ethereum smart contracts through Anvil, providing capabilities to read Solidity code, simulate and execute transactions, manipulate blockchain state, query events, and test contracts in isolated environments for development and auditing workflows.

Enables AI agents and test runners to control Android devices via local ADB, including listing devices, tapping, swiping, typing, sending system keys, launching apps, and dumping UI hierarchy. Communicates over MCP stdio without exposing network listeners.

Enables running SQL warehouse validation checks through natural-language questions in MCP clients, while reusing the same logic for automated pipeline and CI/CD runs.

Enables AI assistants to generate realistic, synthetic test data on demand, including valid PESELs, NIPs, addresses, and more across 27 EU countries, through two tools: list_generators and generate.

Enables AI agents to safely read, search, and inspect a local git repository, including PR-style diffs and changed-file summaries. It also supports opt-in allowlisted test runs.

Provides AI assistants with token-efficient access to Google Play Android Vitals, enabling them to diagnose ANRs, track crashes, analyze startup performance, and compare app versions for release optimizations.

Enables AI assistants to query the Google Play Developer Reporting API for Android production stability data, including crash and ANR issue clusters, de-obfuscated stack traces, release track discovery, startup and crash metric trends, version-to-version comparisons, and anomaly alerts. It also provides guided prompts for incident triage, baseline profile verification, and weekly stability reporting with built-in token compression and caching.

Generates fixed-length test data records with customizable field types including strings, enums, integers, dates, and fillers. Helps developers create realistic test datasets with specified formats and constraints.